//! # Minkowski Distance
//!
//! The Minkowski distance of order _p_ (where _p_ is an integer) is a metric in a normed vector space which can be considered as a generalization of both the Euclidean distance and the Manhattan distance.
//! The Manhattan distance between two points \\(x \in ℝ^n \\) and \\( y \in ℝ^n \\) in n-dimensional space is defined as:
//!
//! \\[ d(x, y) = \left(\sum_{i=0}^n \lvert x_i - y_i \rvert^p\right)^{1/p} \\]
//!
//! Example:
//!
//! ```
//! use smartcore::metrics::distance::Distance;
//! use smartcore::metrics::distance::minkowski::Minkowski;
//!
//! let x = vec![1., 1.];
//! let y = vec![2., 2.];
//!
//! let l1: f64 = Minkowski::new(1).distance(&x, &y);
//! let l2: f64 = Minkowski::new(2).distance(&x, &y);
//!
//! ```
//!
//!
#[cfg(feature = "serde")]
use serde::{Deserialize, Serialize};
use std::marker::PhantomData;
use crate::linalg::basic::arrays::ArrayView1;
use crate::numbers::basenum::Number;
use super::Distance;
/// Defines the Minkowski distance of order `p`
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
#[derive(Debug, Clone)]
pub struct Minkowski {
/// order, integer
pub p: u16,
_t: PhantomData,
}
impl Minkowski {
/// instatiate the initial structure
pub fn new(p: u16) -> Minkowski {
Minkowski { p, _t: PhantomData }
}
}
impl> Distance for Minkowski {
fn distance(&self, x: &A, y: &A) -> f64 {
if x.shape() != y.shape() {
panic!("Input vector sizes are different");
}
if self.p < 1 {
panic!("p must be at least 1");
}
let p_t = self.p as f64;
let dist: f64 = x
.iterator(0)
.zip(y.iterator(0))
.map(|(&a, &b)| (a - b).to_f64().unwrap().abs().powf(p_t))
.sum();
dist.powf(1f64 / p_t)
}
}
#[cfg(test)]
mod tests {
use super::*;
#[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
#[test]
fn minkowski_distance() {
let a = vec![1., 2., 3.];
let b = vec![4., 5., 6.];
let l1: f64 = Minkowski::new(1).distance(&a, &b);
let l2: f64 = Minkowski::new(2).distance(&a, &b);
let l3: f64 = Minkowski::new(3).distance(&a, &b);
assert!((l1 - 9.0).abs() < 1e-8);
assert!((l2 - 5.19615242).abs() < 1e-8);
assert!((l3 - 4.32674871).abs() < 1e-8);
}
#[test]
#[should_panic(expected = "p must be at least 1")]
fn minkowski_distance_negative_p() {
let a = vec![1., 2., 3.];
let b = vec![4., 5., 6.];
let _: f64 = Minkowski::new(0).distance(&a, &b);
}
}